AI Engineer

Jobtailor; Zürich; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

Jobtailor in Zürich seeks an experienced AI/data engineer to scope and lead production-grade AI initiatives.

You will build data pipelines, automate processes, and develop AI-enabled workflows within a regulated environment, collaborating with Compliance, Trading, and Operations teams.

Qualifikationen

• 3–6 years of relevant experience; shipped work is more important than title.
• Production experience with LLM applications, including structured extraction with LLMs and agentic patterns such as tool use and multi-step workflows.
• Strong Python and ability to build production-ready code, not just notebooks.
• Working knowledge of LLM evaluation discipline, including eval sets, regression tests, observability, retrieval, and hallucination handling.
• Familiarity with at least one orchestrator: Dagster, Airflow, or Prefect.
• Familiarity with at least one transformation framework: SQLMesh or dbt.
• Solid SQL, including window functions, joins, and query design.
• Cloud experience, ideally GCP and BigQuery.
• Genuine curiosity about regulated environments and their requirements.
• Professional proficiency in English; German is a plus.
• Eligibility to work in Switzerland, with a Swiss permit or EU/EFTA citizenship.
• Ability to choose simple, appropriate solutions and distinguish AI problems from dashboard, process, or deterministic-script problems.
• Ability to run stakeholder workshops and write production code.
• Serious approach to documentation, evaluation, and audit trails.
• Prior exposure to regulated financial services, crypto, or comparable model-risk environments is nice to have.

Aufgaben

• Identify, scope, and prioritize AI and automation use cases with stakeholders across Compliance, Trading, Operations, Legal, Sales, and Finance.
• Engineer production data solutions, including deterministic automations, AI agents, RAG systems over internal documents, and structured extraction pipelines.
• Build the firm\'s innovation lab environment for prototyping and evaluating new use cases.
• Maintain reusable, version-controlled prompt and skill libraries.
• Maintain the firm-wide inventory of AI systems and use cases.
• Operate the AI approval process through documentation, risk classification, model cards, and evaluation artifacts.
• Conduct technical reviews of new AI initiatives and advise on scope, risk, and design choices.
• Contribute to ELT pipelines using Dagster, SQLMesh, and dlt.
• Build data infrastructure for AI workloads, including feature views, document indexes, and structured event tables.
• Maintain infrastructure as code in Git with review and deployment standards.

Kenntnisse

Production data engineering

LLM applications

Python programming

Dagster

SQLMesh

BigQuery

GCP

Regulated environments curiosity

English proficiency

Tools

Dagster

SQLMesh

BigQuery

Git

Jobbeschreibung

• Identify, scope, and prioritize AI and automation use cases with stakeholders across Compliance, Trading, Operations, Legal, Sales, and Finance


• Engineer production data solutions, including deterministic automations, AI agents, RAG systems over internal documents, and structured extraction pipelines


• Build the firm\'s innovation lab environment for prototyping and evaluating new use cases


• Maintain reusable, version-controlled prompt and skill libraries


• Maintain the firm-wide inventory of AI systems and use cases


• Operate the AI approval process through documentation, risk classification, model cards, and evaluation artifacts


• Conduct technical reviews of new AI initiatives and advise on scope, risk, and design choices


• Contribute to ELT pipelines using Dagster, SQLMesh, and dlt


• Build data infrastructure for AI workloads, including feature views, document indexes, and structured event tables


• Maintain infrastructure as code in Git with review and deployment standards

Requirements

• 3–6 years of relevant experience; shipped work is more important than title


• Demonstrable production experience with LLM applications, including structured extraction with LLMs and agentic patterns such as tool use and multi-step workflows


• Strong Python and ability to build production-ready code, not just notebooks


• Working knowledge of LLM evaluation discipline, including eval sets, regression tests, observability, retrieval, and hallucination handling


• Familiarity with at least one orchestrator: Dagster, Airflow, or Prefect


• Familiarity with at least one transformation framework: SQLMesh or dbt


• Solid SQL, including window functions, joins, and query design


• Cloud experience, ideally GCP and BigQuery


• Genuine curiosity about regulated environments and their requirements


• Professional proficiency in English; German is a plus


• Eligibility to work in Switzerland, with a Swiss permit or EU/EFTA citizenship


• Ability to choose simple, appropriate solutions and distinguish AI problems from dashboard, process, or deterministic-script problems


• Ability to run stakeholder workshops and write production code


• Serious approach to documentation, evaluation, and audit trails


• Prior exposure to regulated financial services, crypto, or comparable model-risk environments is nice to have

Core Competencies

Demonstrates expertise in building and maintaining AI and automation solutions, with a strong focus on production data engineering, LLM applications, and compliance within regulated environments. Proficient in stakeholder engagement, documentation, and the development of robust data infrastructure for AI workloads.

Highest-signal resume keywords

• Production Experience With LLM Applications


• Strong Python Programming


• Familiarity With Dagster Orchestrator


• Solid SQL Skills


• Cloud Experience With GCP

ATS Optimization Keywords

Hard Skills

• Production Data Engineering


• Structured Extraction With LLMs


• Feature Views Development


• Version-Controlled Prompt Libraries


• Risk Classification


• Technical Review of AI Initiatives


• Documentation and Audit Trails


• Multi-Step Workflows


• Deterministic Automations


• AI Workload Infrastructure

Soft Skills

• Stakeholder Engagement


• Curiosity About Regulated Environments


• Workshop Facilitation


• Problem-Solving


• Documentation Approach

Industry Keywords

• Regulated Financial Services


• Model-Risk Environments


• Compliance


• Crypto


• AI Systems Inventory

Tools & Technologies

• Dagster


• SQLMesh


• BigQuery


• Git


• AI Approval Process Tools